code: def hybrid_forward(self, F, input_item, item_valid_length=None):
      item_embed_out = self.embedding(input_item)
      item_encoding, item_att = self.item_encoder(
          inputs=item_embed_out, valid_length=item_valid_length
      )
      item_out = self.item_pooling_dp(item_encoding)
      item_out = self.dense(item_out)
  
      return item_out
  
file_path: analytics-zoo/pyzoo/zoo/models/recommendation/txt.py
imports: from mxnet import gluon
  from gluonnlp.model.transformer import TransformerEncoder, TransformerEncoderCell
label_desc: Use image node_id 2 for calling the SequenceTransformer obj's underlying member method code with example usage: obj.hybrid_forward(F, input_item, item_valid_length) and returns: item_out